S. Jin

Pure dark red emission (650-670 nm) of NaYF(4):Yb/Er upconversion nanoparticles (UCNPs) is achieved by manganese ions (Mn(2+)) doping. In addition, the Mn(2+)-doping can also control the crystalline phase and size of the resulting UCNPs simultaneously. Drug delivery studies suggest the promise of these UCNPs as drug carriers for intracellular drug delivery and eventually as a multifunctional nanoplatform for simultaneous diagnosis and therapy.

The dispersive properties of the atomic transition in the rubidium ${D}_{2}$ line ($5{S}_{\frac{1}{2}}\ensuremath{-}5{P}_{\frac{3}{2}}$) at 780.0 nm are measured with a Mach-Zehnder interferometer when an additional coupling field at 775.8 nm is applied to an upper transition ($5{P}_{\frac{3}{2}}\ensuremath{-}5{D}_{\frac{5}{2}}$). This ladder-type system is observed to exhibit electromagnetically induced transparency together with a rapidly varying refractive index. A reduction in group velocity for the probe beam (${v}_{g}=\frac{c}{13.2}$) is inferred from the measured dispersion curve with 52.5% suppressed absorption on resonance.

We develop a theory of electromagnetically induced transparency in a three-level, ladder-type Doppler-broadened medium, paying special attention to the case where the coupling and probe beams are counterpropagating and have similar frequencies, so as to reduce the total Doppler width of the two-photon process. The theory is easily generalized to deal with the \ensuremath{\Lambda} configuration, where the ideal arrangement involves two copropagating beams. We discuss different possible regimes, depending on the relative importance of the various broadening mechanisms, and identify ways to optimize the absorption-reduction effect. The theory is compared to the results of a recent experiment (on a ladder-type system), using the Rb D2 line, with generally very good agreement. The maximum absorption reduction observed (64.4%) appears to be mostly limited by the relatively large (\ensuremath{\sim}5 MHz) linewidth of the diode lasers used in our experiment.

Abstract Metal–organic frameworks (MOFs), as a promising rechargeable electrochemical energy storage material have emerged in the field of solid‐state lithium batteries. However, low ionic conductivity and high interfacial impedance still severely hamper the application of MOF‐based solid‐state electrolytes (SSE). In this work, a novel hierarchical porous H‐ZIF‐8 solid‐state electrolyte (SSE) material is harvested through the in situ growth of zinc nitrate hydroxide nanosheets, expressing excellent ion conductivity of 1.04 × 10 −3 S cm −1 and Li + ‐transference number of 0.71. Moreover, the morphology and structure of H‐ZIF‐8 is further optimized to obtain a composite H‐ZIF‐8/HNT by decorating halloysite nanotubes (HNT). Notably, functionalized H‐ZIF‐8/HNT as an electrolyte presents obvious enhancement on electrochemical properties: higher ionic conductivity of 7.74 × 10 −3 S cm −1 , better single‐ion transmittability ( = 0.84), good interfacial compatibility as well as excellent rate performance. More importantly, the Li/LiFePO 4 battery equipped with H‐ZIF‐8/HNT SSE has efficient lithium‐dendrite suppression and up to 84% capacity retention (104.16 mA h g −1 ) after 200 times galvanostatic charge/discharge cycles. This work enriches the solid‐state lithium‐ion composite electrolyte materials, opening an entirely new way for enhancing electrochemical performance.

Abstract Under 980 nm near‐infrared (NIR) excitation, upconversion luminescent (UCL) emission of GdF 3 :Yb,Er upconversion nanoparticles (UCNPs) synthesized by a simple and green hydrothermal process can be tuned from yellow to red by varying the concentration of dopant Li + ions. A possible mechanism for enhanced red upconverted radiation is proposed. A layer of silica was coated onto the surface of GdF 3 :Yb,Er,Li UCNPs to improve their biocompatibility. The silica‐coated GdF 3 :Yb,Er,Li UCNPs show great advantages in cell labeling and in vivo optical imaging. Moreover, GdF 3 UCNPs also exhibited a positive contrast effect in T 1 ‐weighted magnetic resonance imaging (MRI). These results suggest that the GdF 3 UCNPs could act as dual‐modality biolabels for optical imaging and MRI.

Rare-earth (RE)-doped gadolinium oxide (Gd2O3) hollow nanospheres have been successfully prepared on a large scale via a template-directed method using hydrothermal carbon spheres as sacrificed templates. Scanning electron microscope and transmission electron microscope images reveal that these hollow-structured nanospheres have the mesoporous shells that are composed of a large amount of uniform nanoparticles. By doping the RE ions (Yb/Er) into the Gd2O3 host matrix, these NPs emitted bright multicolored upconversion emissions that can be fine-tuned from green to red by adjusting the codoped Yb/Er ratio under 980 nm NIR laser excitation. The possibility of using these upconversion nanoparticles for optical imaging in vivo has been demonstrated. It was also shown that these Gd2O3 nanospheres brightened the T1-weighted images and enhanced the r1 relaxivity of water protons, which suggested that they could act as T1 contrast agents for magnetic resonance (MR) imaging. Moreover, these hollow spheres can be used as drug delivery host carriers, and drug storage/release properties were investigated using ibuprofen as the model drug. As a result, the so-prepared nanoscaled Gd2O3 hollow spheres bearing upconversion luminescence, MR imaging, and drug delivery capabilities could be potentially employed for simultaneous MR/fluorescent imaging and therapeutic applications.

Lanthanide (Ln3+) doped Gd2O3 nanoparticles (NPs) have been prepared via a thermal treatment of gadolinium carbonate precursor, which was obtained by simple hydrothermal treatment of Gd(NO3)3 solution in the presence of urea and glycerol. The size of the nanoparticles could be fine tuned from 270 to 10 nm by varying the amount of glycerol, which acted as a chelating agent to control the size of the nanoparticles. Calcination of the gadolinium carbonate nanoparticles at 500 °C led to the formation of uniform Gd2O3 nanoparticles without any obvious morphology change. By doping the lanthanide ions (Yb, Er/Tm) into the Gd2O3 host matrix, these nanoparticles emitted strong upconversion (UC) fluorescence under 980 nm near infrared (NIR) excitation. Moreover, their emission colors could be tuned by simply changing either the co-dopant concentration or the dopant species. Water dispersibility was achieved by forming a silica layer on the surface of the Gd2O3 nanoparticles. The possibility of using these silica-coated upconversion nanoparticles for optical imaging in vitro/in vivo has been demonstrated. It was also shown that these Gd2O3 nanoparticles brightened the T1-weighted images and enhanced r1 relaxivity of water protons, which suggested they act as T1 contrast agents for magnetic resonance (MR) imaging. Thus, Gd2O3 nanoparticles doped with Ln3+ ions provide the dual modality of optical and magnetic resonance imaging.

Hadronic transitions of χcJ→ηcπ+π− (J=0, 1, 2) are searched for using a sample of 1.06×108 ψ(3686) events collected with the BESIII detector at the BEPCII storage ring. The ηc is reconstructed with K0SK±π∓ and K+K−π0 final states. No signals are observed in any of the three χcJ states in either ηc decay mode. At the 90% confidence level, the upper limits are determined to be B(χc0→ηcπ+π−)<0.07%, B(χc1→ηcπ+π−)<0.32%, and B(χc2→ηcπ+π−)<0.54%. The upper limit of B(χc1→ηcπ+π−) is lower than the existing theoretical prediction by almost an order of magnitude. The branching fractions of χcJ→K0SK±π∓π+π−, K+K−π+π−π0, ωK+K−, and ϕπ+π−π0 J=0, 1, 2) are measured for the first time.Received 23 August 2012DOI:https://doi.org/10.1103/PhysRevD.87.012002© 2013 American Physical Society

Lanthanide ion doped GdVO4 upconversion nanoparticles (UCNPs) have been synthesized via a simple hydrothermal process assisted with polyvinylpyrrolidone (PVP). The PVP had great effects on the morphology and luminescent intensity of the final products. Multicolor upconversion emissions such as orange, yellow, green and blue light can be generated by simply changing the codopant compositions or concentrations in these nanoparticles. A thin layer of silica was coated onto the surface of GdVO4 UCNPs to form a core/shell structure in order to improve their biocompatibility. The applications of the low-toxicity, silica-coated GdVO4 UCNPs as bio-tag for cell labeling and in vivo animal imaging were reported. In addition, the GdVO4 nanoparticles showed high contrast T1-enhancing modality due to the presence of Gd3+ ions on the particle surface. Hence, this newly developed multicolor GdVO4 UCNPs, which can be added into the upconversion nanomaterials family, could be used as a promising nanoprobe for dual-modality with optical bioimaging and magnetic resonance imaging (MRI).

Quantum dots (QDs) are a group of semiconducting nanomaterials with unique optical and electronic properties. They have distinct advantages over traditional fluorescent organic dyes in chemical and biological studies in terms of tunable emission spectra, signal brightness, photostability, and so forth. Currently, the major type of QDs is the heavy metal-containing II-IV, IV-VI, or III-V QDs. Silicon QDs and conjugated polymer dots have also been developed in order to lower the potential toxicity of the fluorescent probes for biological applications. Aqueous solubility is the common problem for all types of QDs when they are employed in the biological researches, such as in vitro and in vivo imaging. To circumvent this problem, ligand exchange and polymer coating are proven to be effective, besides synthesizing QDs in aqueous solutions directly. However, toxicity is another big concern especially for in vivo studies. Ligand protection and core/shell structure can partly solve this problem. With the rapid development of QDs research, new elements and new morphologies have been introduced to this area to fabricate more safe and efficient QDs for biological applications.

Here, dual-modal bioprobes for combined optical and magnetic resonance (MR) imaging are reported. Gadolinium orthophosphate (GdPO(4)) nanorods co-doped with light-emitting lanthanide ions have been successfully prepared through a hydrothermal method. An efficient downconversion luminescence from Ce/Tb or Eu doped GdPO(4) nanorods and upconversion luminescence from Yb/Er co-doped GdPO(4) nanorods are observed, respectively, which offers the optical modality for the nanoprobes. Notably, we first report the upconversion phenomenon based on the GdPO(4) matrix under 980 nm near infrared irradiation. The possibility of using these nanoprobes with downconversion and upconversion luminescent emissions for optical cell imaging is also demonstrated. Furthermore, these Gd(3+)-containing nanophosphors show good positive signal-enhancement ability when performed under a 4.7 T MR imaging scanner, indicating they have potential as T(1) MR imaging contrast agents. Thus, nanoprobes based on GdPO(4) nanophosphors are shown to provide the dual modality of optical and MR imaging.

The discovery of the Higgs boson with its mass around 125 GeV by the ATLAS and CMS Collaborations marked the beginning of a new era in high energy physics. The Higgs boson will be the subject of extensive studies of the ongoing LHC program. At the same time, lepton collider based Higgs factories have been proposed as a possible next step beyond the LHC, with its main goal to precisely measure the properties of the Higgs boson and probe potential new physics associated with the Higgs boson. The Circular Electron Positron Collider (CEPC) is one of such proposed Higgs factories. The CEPC is an e+e− circular collider proposed by and to be hosted in China. Located in a tunnel of approximately 100 km in circumference, it will operate at a center-of-mass energy of 240 GeV as the Higgs factory. In this paper, we present the first estimates on the precision of the Higgs boson property measurements achievable at the CEPC and discuss implications of these measurements.

By using a commercially available surfactant (TWEEN), we report a simple and efficient method to convert hydrophobic NaYF4:Yb,Er/NaYF4 core/shell upconversion nanoparticles to hydrophilic ones for bioimaging and drug delivery.

In order to produce water-dispersible nanocrystals, including upconversion nanoparticles (UCNPs) which are the new generation fluorophores and magnetic nanoparticles (Fe3O4), a polyethylenimine-modified graphene oxide (PEI-GO) was used as a nanocarrier of nanocrystals, and PEI-GO-nanocrystal hybrids were prepared by transferring hydrophobic nanocrystals from an organic phase to water. Nanocrystals were anchored onto the hydrophobic plane of PEI-GO, which was confirmed by atomic force microscopy and electron microscopy. Molecular dynamics simulation further showed that hydrophobic interaction between PEI-GO and oleic acid molecules coated on the surface of the nanocrystals was the major driving force in the transfer process. The resulting hybrids had high stability in both water and physiological solutions, and combined the functionalities of the nanocrystals and PEI-GO, such as luminescence, superparamagnetism and drug delivery capability. Through π–π stacking interaction between PEI-GO-UCNP and an aromatic drug, PEI-GO-UCNP was able to load a water-insoluble anticancer drug, doxorubicin (DOX), with a superior loading capacity of 100 wt.%. In addition, PEI-GO-UCNP did not exhibit toxicity on the human endothelial cells and PEI-GO-UCNP-DOX showed a high potency of killing cancer cells in vitro.

Coverage path planning (CPP) of multiple Dubins robots has been extensively applied in aerial monitoring, marine exploration, and search and rescue. Existing multi-robot coverage path planning (MCPP) research use exact or heuristic algorithms to address coverage applications. However, several exact algorithms always provide precise area division rather than coverage paths, and heuristic methods face the challenge of balancing accuracy and complexity. This paper focuses on the Dubins MCPP problem of known environments. Firstly, we present an exact Dubins multi-robot coverage path planning (EDM) algorithm based on mixed linear integer programming (MILP). The EDM algorithm searches the entire solution space to obtain the shortest Dubins coverage path. Secondly, a heuristic approximate credit-based Dubins multi-robot coverage path planning (CDM) algorithm is presented, which utilizes the credit model to balance tasks among robots and a tree partition strategy to reduce complexity. Comparison experiments with other exact and approximate algorithms demonstrate that EDM provides the least coverage time in small scenes, and CDM produces a shorter coverage time and less computation time in large scenes. Feasibility experiments demonstrate the applicability of EDM and CDM to a high-fidelity fixed-wing unmanned aerial vehicle (UAV) model.

Regeneration of injured articular cartilage is limited by low early-stage recruitment of stem cells and insufficient chondrogenic differentiation. Hydrogels are widely used to repair cartilage because they have excellent mechanical and biological properties. In this study, a dual drug-loaded thermosensitive hydroxypropyl chitin hydrogel (HPCH) system was prepared to release stromal-derived factor-1α-like polypeptides (SDFP) and kartogenin (KGN) for stem-cell recruitment and chondrogenic differentiation. The hydrogel had a network structure that promoted cell growth and nutrient exchange. Moreover, it was temperature sensitive and suitable for filling irregular defects. The system showed good biocompatibility in vitro and promoted stem-cell recruitment and chondrogenic differentiation. Furthermore, it reduced chondrocyte catabolism under inflammatory conditions. Animal experiments demonstrated that the dual-drug hydrogel systems can promote the regeneration of articular cartilage in rats. This study confirmed that an HPCH system loaded with KGN and SDFP could effectively repair articular cartilage defects and represents a viable treatment strategy.

Cartilage has limited self-repair ability, leading to osteoarthritis postinjury and ultimately physical disability in people. In addition, cartilage injury is accompanied by loss of extracellular matrix (ECM) and infiltration of inflammation, which makes cartilage regeneration more difficult. In this study, a hybrid hydrogel of hydroxypropyl chitin and oxidized chondroitin sulfate (HPCH-OCS) with injectable and thermosensitive properties was prepared by a Schiff base reaction. In vitro, the HPCH-OCS hydrogel showed desirable biocompatibility and bioactivity by promoting chondrogenic differentiation of stem cells, maintaining the chondrocyte phenotype, and inhibiting proteins related to cartilage ECM catabolism under inflammatory conditions. In vivo, the HPCH-OCS hydrogel combined with microfracture could effectively repair cartilage defects and promote cartilage regeneration. In conclusion, the HPCH-OCS hydrogel has good biological and mechanical properties, and its combination with microfracture provides an effective strategy for clinical cartilage regeneration.

We report the availability of a digitized Chinese male and a digitzed Chinese female typical of the population and with no obvious abnormalities. The embalming and milling procedures incorporate three technical improvements over earlier digitized cadavers. Vascular perfusion with coloured gelatin was performed to facilitate blood vessel identification. Embalmed cadavers were embedded in gelatin and cryosectioned whole so as to avoid section loss resulting from cutting the body into smaller pieces. Milling performed at -25 degrees C prevented small structures (e.g. teeth, concha nasalis and articular cartilage) from falling off from the milling surface. The male image set (.tiff images each of 36 Mb) has a section resolution of 3072 x 2048 pixels ( approximately 170 micro m, the accompanying magnetic resonance imaging and computer tomography data have a resolution of 512 x 512, i.e. approximately 440 micro m). The Chinese Visible Human male and female datasets are available at http://www.chinesevisiblehuman.com. (The male is 90.65 Gb and female 131.04 Gb). MPEG videos of direct records of real-time volume rendering are at: http://www.cse.cuhk.edu.hk/~crc

Based on 58 million BESII J/ψ events, the K¯∗(892)0K+π− channel in K+K−π+π− is studied. A clear low mass enhancement in the invariant mass spectrum of K+π− is observed. The low mass enhancement does not come from background of other J/ψ decay channels, nor from phase space. Two independent partial wave analyses have been performed. Both analyses favor that the low mass enhancement is the κ, an iso-spinor scalar resonant state. The average mass and width of the κ in the two analyses are 878±23−55+64MeV/c2 and 499±52−87+55MeV/c2, respectively, corresponding to a pole at (841±30−73+81)−i(309±45−72+48)MeV/c2.

The decays $J/\psi \rightarrow \gamma \pi^+\pi^-\pi^0$ and $J/\psi \rightarrow \gamma \pi^0\pi^0\pi^0$ are analyzed using a sample of 225 million $\jpsi$ events collected with the BESIII detector. The decay of $\eta(1405)\ar f_{0}(980)\pi^0$ with a large isospin violation is observed for the first time. The width of the $f_{0}(980)$ observed in the dipion mass spectra is anomalously narrower than the world average. Decay rates for three-pion decays of the $\eta'$ are also measured precisely.

The utilization of up-conversion nanoparticles (UCNPs) for photodynamic therapy (PDT) has gained significant interest due to their unique ability to convert near infrared light to UV/visible light. Previous work mainly focused on the fabrication of green and red emitting UCNPs to load photosensitizers (PSs) for PDT. In this work, we firstly developed a new multifunctional nanoplatform combining blue-emitting UCNPs with blue-light excited PS (hypocrellin A, HA) as a NIR photosensitizing nanoplatform for PDT of cancer cells. Tween 20 coated NaYbF4:Tm, Gd@NaGdF4 UCNPs (Tween 20-UCNPs) with strong blue up-conversion luminescence and good water dispersibility were prepared for use as PS carriers. The blue emission band matched well with the efficient absorption band of HA, thereby facilitating the resonance energy transfer from UCNPs to HA and then activating HA to produce singlet oxygen (1O2). The in vitro study showed that these Tween 20-UCNPs@HA complexes could efficiently produce 1O2 to kill cancer cells under 980 nm NIR excitation. Moreover, these Gd3+ and Yb3+ containing nanoparticles also exhibited positive contrast effects in both T1 weighted magnetic resonance imaging (MRI) and computed tomography (CT) imaging, making them become a multifunctional platform for simultaneous PDT and bio-imaging.

The numbers of $\psi(3686)$ events accumulated by the BESIII detector for the two rounds of data taking during 2009 and 2012 are determined to be $(107.0\pm0.8)\times 10^6$ and $(341.1\pm 2.1)\times 10^6$, respectively, by counting inclusive hadronic events, where the uncertainty is dominated by systematics and the statistical uncertainty is negligible. The number of events for the sample taken in 2009 is consistent with that of the previous measurement. The total number of $\psi(3686)$ events for the two data-taking periods is $(448.1\pm2.9)\times10^6$.

Cell lines play an important role in studying biological processes in vitro. In this study, we aimed to establish and characterize the first cell line isolated from the small yellow croaker (Larimichthys polyactis), an economically important marine fish in China. The small yellow croaker fry (SYCF) cells proliferated well in Leibovitz's 15 medium containing 2% antibiotics, 0.1 M NaCl, and 10% fetal bovine serum at 27 °C. Sequence analyses of mitochondrial genes confirmed the origin of SYCF cells. Furthermore, we unraveled the mechanism of hypoxia-induced apoptosis, a major threat to aquatic animals using the SYCF cell line. The HIF-PHD pathway of the SYCF cells can be activated under hypoxic stress, suggesting that this cell line is impressible for hypoxia and can serve as a superb model in vitro to study the cell physiology in L. polyactis in a hypoxic setting. We found that hypoxia results in morphological abnormalities, excess reactive oxygen species (ROS) production, and dysfunctional redox homeostasis, indicating the occurrence of oxidative stress in the SYCF cells. In addition, decreased cell viability and severe apoptosis were detected under hypoxic conditions. Through monitoring the indicators of the intrinsic and extrinsic apoptosis pathways, including the mitochondrial membrane potential, the expression of bax, bcl2, bnip3, and fas, Bcl2, and Caspase-3 protein, and activity of Caspases-3/8/9, we found that both pathways are involved. Considering that ROS-induced oxidative stress may be the main reason of apoptosis, we investigated whether the addition of an antioxidant, N-Acetyl-L-cysteine (NAC), will ameliorate the apoptosis. Interestingly, we found that both intrinsic and extrinsic apoptosis indicators were markedly recovered by adding NAC in culture media, significant remissions were also observed in the cell viability and apoptosis rate. These results suggested that hypoxia-induced apoptosis of SYCF cells may be mediated by the overproduction of ROS, and the antioxidant may be a useful material to relieve cell damage under hypoxia in fish. In general, this study established a marine fish cell line of SYCF cells, which can be used as an in vitro research model of L. polyactis and for revealing the mechanisms of ROS-induced apoptosis under hypoxic conditions in this species. This provides important insights into the cellular physiology of marine fish under hypoxia.

Communications on Pure and Applied MathematicsVolume 52, Issue 5 p. 613-654 The semiclassical limit of the defocusing NLS hierarchy Shan Jin, Shan Jin [email protected] Program in Applied Mathematics, University of Arizona, Tucson AZ 85721Search for more papers by this authorC. David Levermore, C. David Levermore amth.arizona.edu University of Arizona, Department of Mathematics, Tucson AZ 85721Search for more papers by this authorDavid W. McLaughlin, David W. McLaughlin [email protected] Courant Institute, 251 Mercer Street, New York, NY 10012Search for more papers by this author Shan Jin, Shan Jin [email protected] Program in Applied Mathematics, University of Arizona, Tucson AZ 85721Search for more papers by this authorC. David Levermore, C. David Levermore amth.arizona.edu University of Arizona, Department of Mathematics, Tucson AZ 85721Search for more papers by this authorDavid W. McLaughlin, David W. McLaughlin [email protected] Courant Institute, 251 Mercer Street, New York, NY 10012Search for more papers by this author First published: 25 March 1999 https://doi.org/10.1002/(SICI)1097-0312(199905)52:5<613::AID-CPA2>3.0.CO;2-LCitations: 90AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinkedInRedditWechat Abstract We establish the semiclassical limit of the one-dimensional defocusing cubic nonlinear Schrödinger (NLS) equation. Complete integrability is exploited to obtain a global characterization of the weak limits of the entire NLS heirarchy of conserved densities as the field evolves from reflectionless initial data under all the associated commuting flows. Consequently, this also establishes the zero-dispersion limit of the modified Korteweg-de Vries equation that resides in that hierarchy. We have adapted and clarified the strategy introduced by Lax and Levermore to study the zero-dispersion limit of the korteweg-de Vries equation, expanding it to treat entire integrable heirarchies and strengthening the limits obtained. A crucial role is played by the convexity of the underlying log-determinant with respect to the times associated with the commuting flows. © 1999 John Wiley & Sons, Inc. Bibliography 1 Bronski, J. C.; McLaughlin, D. W. Semiclassical behavior in the NLS equation: Optical shocks—focusing instabilities. Singular limits of dispersive waves (Lyon, 1991), 21–38. Edited by N. M. Ercolani, I. 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We establish the semiclassical limit of the one-dimensional defocusing cubic nonlinear Schrödinger (NLS) equation. Complete integrability is exploited to obtain a global characterization of the weak limits of the entire NLS heirarchy of conserved densities as the field evolves from reflectionless initial data under all the associated commuting flows. Consequently, this also establishes the zero-dispersion limit of the modified Korteweg-de Vries equation that resides in that hierarchy. We have adapted and clarified the strategy introduced by Lax and Levermore to study the zero-dispersion limit of the korteweg-de Vries equation, expanding it to treat entire integrable heirarchies and strengthening the limits obtained. A crucial role is played by the convexity of the underlying log-determinant with respect to the times associated with the commuting flows. © 1999 John Wiley & Sons, Inc.

Results are presented on ψ(2S) and J/ψ hadronic decays to K0SpK−n̄ and K0S¯pK+n final states from data samples of 14 million ψ(2S) and 58 million J/ψ events accumulated at the BES II detector. No Θ(1540) signal, the pentaquark candidate, is observed, and upper limits are set for B(ψ(2S)→Θ¯Θ→K0SpK−n̄+K0S¯pK+n)<0.84×10−5 and B(J/→ψΘ¯Θ→K0SpK−n̄+K0S¯pK+n)<1.1×10−5 at the 90% confidence level. For single Θ(1540) production, the upper limits determined by our analysis are also on the order of 10−5 in both ψ(2S) and J/ψ decays. Received 4 February 2004DOI:https://doi.org/10.1103/PhysRevD.70.012004©2004 American Physical Society

The United States Visible Human Project (VHP) created a digital image data set of complete human male (data acquisition finished in November 1994) and female (data acquisition finished in December 1995) cadavers in magnetic resonance imaging (MRI), computed tomography (CT), and anatomical (anatomic serial section) modes. VHP aroused worldwide enthusiasm for Visible Human Research (VHR), and the data set is being used in a variety of research and educational domains. The Visible Korean Human (VKH) male was produced in March 2001. To accelerate worldwide VHR and to promote virtual anatomy as a revolutionary break with conventional anatomy, more visible human data sets representative of different populations of the world are in demand. The Chinese Visible Human (CVH) male (created in October 2002) and female (created in February 2003) project achieved greater integrity of images, easier blood vessel identification, and were free of organic lesion (unlike the other visible human projects). We performed data acquisition, three-dimensional (3D) reconstruction, and visualization with improved technology to create CVH male and female. CVH is the first volumetric data representing a complete normal adult human male and female of an Asian population. This article presents the history of Chinese Visible Human cadavers and the methods and technology used to produce the data set.

T helper type 17 (Th17) cells have been implicated in autoimmunity and inflammatory bowel disease (IBD). Antigen-presenting cell (APC) -derived cytokines such as interleukin (IL)-1β and IL-6 are key mediators supporting Th17 differentiation, yet how these factors are induced in vivo remains unclear. Here, we show that IL-27 acting on APCs enhances IL-6 and IL-1β production and Th17 differentiation. IL-27Rα-/- T-cell receptor (TCR)β-/- recipients fail to develop gut inflammation following naive CD4 T-cell transfer, whereas IL-27Rα+/+ TCRβ-/- recipients develop severe colitis. Investigation of T-cell responses exhibits that IL-27Rα-/- TCRβ-/- mice do not support Th17 differentiation with significantly decreased levels of IL-6 and IL-1β by APCs. Our study has identified a novel proinflammatory role for IL-27 in vivo that promotes Th17 differentiation by inducing Th17-supporting cytokines in APCs.

Purpose This study aims to make full use of the advantages of connected and autonomous vehicles (CAVs) and dedicated CAV lanes to ensure all CAVs can pass intersections without stopping. Design/methodology/approach The authors developed a signal coordination model for arteries with dedicated CAV lanes by using mixed integer linear programming. CAV non-stop constraints are proposed to adapt to the characteristics of CAVs. As it is a continuous problem, various situations that CAVs arrive at intersections are analyzed. The rules are discovered to simplify the problem by discretization method. Findings A case study is conducted via SUMO traffic simulation program. The results show that the efficiency of CAVs can be improved significantly both in high-volume scenario and medium-volume scenario with the plan optimized by the model proposed in this paper. At the same time, the progression efficiency of regular vehicles is not affected significantly. It is indicated that full-scale benefits of dedicated CAV lanes can only be achieved with signal coordination plans considering CAV characteristics. Originality/value To the best of the authors’ knowledge, this is the first research that develops a signal coordination model for arteries with dedicated CAV lanes.

Temporal action proposal generation (TAPG) is a challenging task that aims to locate action instances in untrimmed videos with temporal boundaries. To evaluate the confidence of proposals, the existing works typically predict action score of proposals that are supervised by the temporal Intersection-over-Union (tIoU) between proposal and the ground-truth. In this paper, we innovatively propose a general auxiliary Background Constraint idea to further suppress low-quality proposals, by utilizing the background prediction score to restrict the confidence of proposals. In this way, the Background Constraint concept can be easily plug-and-played into existing TAPG methods (BMN, GTAD). From this perspective, we propose the Background Constraint Network (BCNet) to further take advantage of the rich information of action and background. Specifically, we introduce an Action-Background Interaction module for reliable confidence evaluation, which models the inconsistency between action and background by attention mechanisms at the frame and clip levels. Extensive experiments are conducted on two popular benchmarks, ActivityNet-1.3 and THUMOS14. The results demonstrate that our method outperforms state-of-the-art methods. Equipped with the existing action classifier, our method also achieves remarkable performance on the temporal action localization task.

Rim-driven thruster (RDT) is a new integrated thruster that has attracted much attention recently. The RDT provides the benefits of reducing vibration and noise and increasing useable volume by mounting the propulsion motor stator into the duct and fusing the motor rotor with the propeller blades. The calculation method of RDT considering the motor gap was discussed and validated. A simulation-based design optimization framework was proposed for the particularity of RDT ducts. The parametric reconstruction of the duct was executed based on the Bézier curve. The optimal Latin hypercube design method was used to generate samples, and the approximate model was developed based on the radial basis function (RBF) neural network. The fitting R2 of efficiency, minimum pressure, blade thrust, and total thrust of the approximate model reached 0.998, 0.955, 0.998, and 0.990, respectively. On this basis, the NSGA-II was employed to optimize the duct with minimum pressure and efficiency as the optimization objectives. Sensitivity analyses indicate that the optimization objectives are significantly affected by the nozzle size, followed by the internal nozzle profile. The typical Pareto solutions were verified by CFD calculation, and the duct optimization can improve efficiency by 3.3% or minimum pressure by 5.3%.

Abstract High-spatial-resolution observations of CO isotopologue line emission in protoplanetary disks at mid-inclinations (≈30°–75°) allow us to characterize the gas structure in detail, including radial and vertical substructures, emission surface heights and their dependencies on source characteristics, and disk temperature profiles. By combining observations of a suite of CO isotopologues, we can map the two-dimensional ( r , z ) disk structure from the disk upper atmosphere, as traced by CO, to near the midplane, as probed by less abundant isotopologues. Here, we present high-angular-resolution (≲0.″1 to ≈0.″2; ≈15–30 au) observations of CO, 13 CO, and C 18 O in either or both J = 2–1 and J = 3–2 lines in the transition disks around DM Tau, Sz 91, LkCa 15, and HD 34282. We derived line emission surfaces in CO for all disks and in 13 CO for the DM Tau and LkCa 15 disks. With these observations, we do not resolve the vertical structure of C 18 O in any disk, which is instead consistent with C 18 O emission originating from the midplane. Both the J = 2–1 and J = 3–2 lines show similar heights. Using the derived emission surfaces, we computed radial and vertical gas temperature distributions for each disk, including empirical temperature models for the DM Tau and LkCa 15 disks. After combining our sample with literature sources, we find that 13 CO line emitting heights are also tentatively linked with source characteristics, e.g., stellar host mass, gas temperature, disk size, and show steeper trends than seen in CO emission surfaces.

Lung cancer combined by chronic obstructive pulmonary disease (LC-COPD) is a common comorbidity and their interaction with each other poses significant clinical challenges. However, there is a lack of well-established consensus on the diagnosis and treatment of LC-COPD.A panel of experts, comprising specialists in oncology, respiratory medicine, radiology, interventional medicine, and thoracic surgery, was convened. The panel was presented with a comprehensive review of the current evidence pertaining to LC-COPD. After thorough discussions, the panel reached a consensus on 17 recommendations with over 70% agreement in voting to enhance the management of LC-COPD and optimize the care of these patients.The 17 statements focused on pathogenic mechanisms (n=2), general strategies (n=4), and clinical application in COPD (n=2) and lung cancer (n=9) were developed and modified. These statements provide guidance on early screening and treatment selection of LC-COPD, the interplay of lung cancer and COPD on treatment, and considerations during treatment. This consensus also emphasizes patient-centered and personalized treatment in the management of LC-COPD.The consensus highlights the need for concurrent treatment for both lung cancer and COPD in LC-COPD patients, while being mindful of the mutual influence of the two conditions on treatment and monitoring for adverse reactions.

Mn-based layered oxides have been considered the most promising cathode candidates for cost-effective potassium-ion batteries (PIBs). Herein, equiatomic constituents of Ni, Fe, Mg, and Ti have been introduced into the transition metal layers of Mn-based layered oxide to design a high-entropy K0.6Ni0.05Fe0.05Mg0.05Ti0.05Mn0.0725O2 (HE-KMO, S = 1.17R). Consequently, the experimental results manifest that the layered structure of HE-KMO is more stable than conventional low-entropy K0.6MnO2 (LE-KMO, S = 0.66R) during successive cycling and even upon exposure to moisture. Diffraction and electrochemical measurements reveal that HE-KMO undergoes a solid-solution mechanism, contrary to the multistage phase transition processes typically exemplified in K0.6MnO2. Benefiting from the stabilized high-entropy layered framework and the solid-solution K+ storage mechanism, the entropy-stabilized HE-KMO not only demonstrates exceptional rate capability but also shows excellent cyclic stability. Notably, a capacity retention ratio of 86% after 3000 cycles can still be sustained at a remarkable current density of 5000 mA g-1.

Patients with intermediate-risk non-muscle-invasive bladder cancer (IR NMIBC) have a high risk of recurrence and need effective therapies to reduce the risk of disease recurrence or progression. This phase 1b study (NCT02720367) assessed the safety and tolerability of TAR-200, an intravesical drug delivery system, in participants with IR NMIBC.Participants with recurrent IR NMIBC were eligible. Participants received either two 7-d or two 21-d TAR-200 dosing cycles over a 4-6-wk period in a marker lesion/ablation design. TAR-200 was placed in the window between the cystoscopy showing recurrent papillary disease and the subsequent complete transurethral resection of the bladder tumour. The primary endpoint was TAR-200 safety. The secondary endpoints included TAR-200 tolerability, pharmacokinetics, and preliminary efficacy.Twelve participants received TAR-200 treatment. No TAR-200-related serious or grade ≥ 3 treatment-emergent adverse events (TEAEs) occurred. Nine participants had grade ≤ 2 TAR-200-related TEAEs, with urgency, dysuria, and haematuria being most common. Two participants refused a second dosing cycle due to urinary urgency and frequency. Insertion and removal of TAR-200 was successful in all cases. Plasma gemcitabine concentrations remained below the lower limit of detection. Five participants (42%) had complete response (CR): four had pathological CR and one had CR based on visual assessment.TAR-200 appears to be safe and well tolerated, with encouraging preliminary efficacy in participants with IR NMIBC. This study lays the groundwork for the multiple phase 2 and 3 global studies that are currently on-going for TAR-200.In this study, researchers evaluated the safety of the novel drug delivery system TAR-200 in participants with intermediate-risk non-muscle-invasive bladder cancer. They concluded that TAR-200 was safe and well tolerated with promising antitumour activity.

By tagging the largest energy of the assumed kaon in the final states of e+e−→hadrons, we measured the cross sections for e+e−→hadrons|non-DD¯ in the range from 3.65 to 3.87 GeV. Analyzing these cross sections yields the branching fraction for the decay ψ(3770)→non-DD¯ to be BF[ψ(3770)→non-DD¯]=(15.1±5.6±1.8)%, and the observed non-DD¯ and DD¯ cross sections to be σhad-non-DD¯obs=(1.08±0.40±0.15) nb and σDD¯obs=(6.07±0.40±0.35) nb, respectively, at the center-of-mass energy Ecm=3.7724 GeV.

Au-Ge-based alloys are interesting as novel high-temperature lead-free solders because of their low melting point, good thermal and electrical conductivity, and high corrosion resistance. In the present work, the wetting and soldering behavior of the eutectic Au-28Ge (at.%) alloy on Cu and Ni substrates have been investigated. Good wetting on both substrates with final contact angles of 13° to 14° was observed. In addition, solder joints with bond shear strength of 30 MPa to 35 MPa could be produced under controlled conditions. Cu substrates exhibit pronounced dissolution into the Au-Ge filler metal. On Ni substrates, the NiGe intermetallic compound was formed at the filler/substrate interface, which prevents dissolution of Ni into the solder. Using thin filler metal foils (25 μm), complete consumption of Ge in the reaction at the Ni interface was observed, leading to the formation of an almost pure Au layer in the soldering zone.

Using samples of 2.25*10^8 J/psi events and 1.06*10^8 psi' events collected with the BES III detector, we study the f0(980) to a0(980) and a0(980) to f0(980) transitions in the processes J/psi --> phi f0(980) --> phi a0(980) and chi_c1 --> pi^0 a0(980) --> pi^0 f0(980), respectively. Evidence for f0(980) --> a0(980) is found with a significance of 3.4 sigma, while in the case of a0(980) --> f0(980) transition, the significance is 1.9 sigma. Measurements and upper limits of both branching ratios and mixing intensities are determined.

Owning to its extremely long endurance, small size, cost-effective employment, easy, and fast transported properties, the merits of autonomous underwater vehicles (AUVs) exceed those of manned underwater vehicles. Therefore, it has become an indispensable member in navies throughout the world, as well as with oceanographic research, commercial resource explorations, and especially the underwater search and rescue (SAR) sectors. Up to date, the tragic MH370 and QZ8501 flight incidents have dramatically increasing the awareness of high-performance SAR equipment, which in turn will stimulate the states party to the incident to urgently upgrade their shallow- and deep-sea SAR equipment. To extend the range (endurance) and shorter the searching period for the next generation SAR AUV, a sea water cooled high-power density magnetically slotless permanent magnet brushless motor is proposed and integrated with pump-jet's impeller to achieve designated shaftless pump-jet propulsor. In this paper, the developed shaftless pump-jet propulsion system is applied in Naval University of Engineering series multi-purpose long-range and high-speed deep-sea AUV, which could provide excellent performance as a SAR platform.

Now, most existing dynamic RGB-D SLAM methods are based on deep learning or mathematical models. Abundant training sample data is necessary for deep learning, and the selection diversity of semantic samples and camera motion modes are closely related to the robust detection of moving targets. Furthermore, the mathematical models are implemented at the feature-level of segmentation, which is likely to cause sub or over-segmentation of dynamic features. To address this problem, different from most feature-level dynamic segmentation based on mathematical models, a non-prior semantic dynamic segmentation based on a particle filter is proposed in this paper, which aims to attain the motion object segmentation. Firstly, GMS and optical flow are used to calculate an inter-frame difference image, which is considered an observation measurement of posterior estimation. Then, a motion equation of a particle filter is established using Gaussian distribution. Finally, our proposed segmentation method is integrated into the front end of visual SLAM and establishes a new dynamic SLAM, PFD-SLAM. Extensive experiments on the public TUM datasets and real dynamic scenes are conducted to verify location accuracy and practical performances of PFD-SLAM. Furthermore, we also compare experimental results with several state-of-the-art dynamic SLAM methods in terms of two evaluation indexes, RPE and ATE. Still, we provide visual comparisons between the camera estimation trajectories and ground truth. The comprehensive verification and testing experiments demonstrate that our PFD-SLAM can achieve better dynamic segmentation results and robust performances.

A 64.4% reduction in absorption at the rubidium D2 line is observed when a pumping field at 775.8 nm is tuned on resonance to the transition between the excited states 5${\mathit{P}}_{3/2}$ and 5${\mathit{D}}_{5/2}$. As the pumping field is tuned off resonance, an absorption peak appears at the side of the Doppler-broadened D2 line. This modification in absorption is related to pumping-induced atomic coherence in this three-level ladder-type system. This experiment is done in a Rb vapor cell at room temperature and with cw diode lasers for both pumping and probe beams in a Doppler-free configuration.

The Ce–Cu binary system has been thermodynamically reassessed by CALPHAD approach based on experimental data and thermodynamic properties of phase diagram. Incorporating the thermodynamic evaluations of Al–Ce and Al–Cu systems from literature, the Al–Ce–Cu ternary system has been assessed using CALPHAD approach. The solution phases including liquid, Fcc and Bcc were treated as substitutional solution phases and the Redlich–Kister polynomial was used to describe their excess Gibbs energies. All binary and ternary intermetallic compounds were treated as stoichiometric phases and their Gibbs energies of formation were optimized. The calculated Al–Ce–Cu phase diagram agreed well with available experimental data.

As an essential constitution of either Cu- or Zr-based bulk metallic glass alloys, the Al–Cu–Zr ternary system has aroused a great attention for decades. Since the three constituent binary systems, Al–Cu, Al–Zr and Cu–Zr, have been optimized previously, the focus of this work was only given to the Al–Cu–Zr ternary system. Based on the experimental enthalpies of mixing of ternary liquid and undercooled liquid alloys as well as the evaluated isothermal sections, the Al–Cu–Zr ternary system has been assessed using the CALPHAD method. Most of the calculated results show good agreement with the experimental thermodynamic data and the reported phase diagrams. By employing the driving force criterion with the present thermodynamic description, the observed glass-forming abilities in the Al–Cu–Zr system can be accounted for satisfactorily.

We present results of a study of the decay J/ψ → ωηπ+ π- using a sample of (225.2 ± 2.8) × 10(6) J/ψ events collected by the BESIII detector, and report the observation of a new process J/ψ → ωX(1870) with a statistical significance of 7.2σ, in which X(1870) decays to a(0)(±)(980)π±. Fitting to ηπ+ π- mass spectrum yields a mass M = 1877.3 ± 6.3(stat)(-7.4)(+3.4)(syst) MeV/c(2), a width Γ = 57 ± 12(stat)(-4)(+19)(syst) MeV/c(2), and a product branching fraction B(J/ψ → ωX) × B(X→a(0)(±)(980)π±) × B(a(0) (±)(980) → ηπ±) = [1.50 ± 0.26(stat)(-0.36)(+0.72) (syst)] × 10(-4). Signals for J/ψ → ωf(1)(1285) and J/ψ → ω η(1405) are also clearly observed and measured.

Social networks have been part of people's daily life and plenty of users have registered accounts in multiple social networks. Interconnections among multiple social networks add a multiplier effect to social applications when fully used. With the sharp expansion of network size, traditional standalone algorithms can no longer support computing on large scale networks while alternatively, distributed and parallel computing become a solution to utilize the data-intensive information hidden in multiple social networks. As such, synergistic partitioning, which takes the relationships among different networks into consideration and focuses on partitioning the same nodes of different networks into same partitions. With that, the partitions containing the same nodes can be assigned to the same server to improve the data locality and reduce communication overhead among servers, which are very important for distributed applications. To date, there have been limited studies on multiple large scale network partitioning due to three major challenges: 1) the need to consider relationships across multiple networks given the existence of intricate interactions, 2) the difficulty for standalone programs to utilize traditional partitioning methods, 3) the fact that to generate balanced partitions is NP-complete. In this paper, we propose a novel framework to partition multiple social networks synergistically. In particular, we apply a distributed multilevel k-way partitioning method to divide the first network into k partitions. Based on the given anchor nodes which exist in all the social networks and the partition results of the first network, using MapReduce, we then develop a modified distributed multilevel partitioning method to divide other networks. Extensive experiments on two real data sets demonstrate that our method can significantly outperform baseline independent-partitioning method in accuracy and scalability.

Hand, foot, and mouth disease (HFMD) is an infectious disease typically caused by enterovirus 71 (EV71) and Coxsackievirus A16. The incidence of HFMD appears to be increasing across the Asia Pacific region, with deaths occurring predominantly among children. Therefore, most HFMD reports focus on children and few have studied HFMD in adults. However, more adult HFMD cases may be seen in the foreseeable future as a result of global warming, continued viral evolution, and an increase in traveling. Thus, this study investigated the clinical and epidemiological characteristics of adult HFMD.Case data of 49 adult HFMD patients who attended The First Affiliated Hospital of Jiaxing College, China from May 2008 to November 2013 were obtained. Socio-demographic data were collected through follow-up phone calls. Throat swab specimens were tested for enterovirus by quantitative reverse transcription-polymerase chain reaction and further confirmed by virus isolation assay. For 10 patients infected with EV71, the gene encoding the EV71 VP1 protein was sequenced and analyzed. Data from 8,354 child HFMD patients and 49 adult patients in the fever clinic of The First Affiliated Hospital of Jiaxing College during the same period were collected for comparison.This study revealed that close contact with HFMD patients and poor personal hygiene consciousness were risk factors for adult HFMD. This study also found that EV71 subgenotype C4a was the most common pathogen associated with adult HFMD in this area. Furthermore, this study demonstrated several unique epidemiological characteristics of adult HFMD compared to child HFMD, such as the geographic and gender distribution of adult HFMD patients and HFMD seasonality.The findings in this study showed the potential threat of adult HFMD.

We investigated the growth and characterization of InGaN films with high In content up to 51.9% obtained by MBE MME-growth. Comparing the structural and optical properties of InGaN films grown using common growth method and MME technique, we could acquire the good quality of InGaN sample by MME-growth method with lower dislocation density, better composition uniformity and smoother surface. These experimental results suggest that MME has an enormous potential to promote the quality of high In-content InGaN materials and the development of InGaN-based devices. Besides, further study shows the process of MME growth, the parameters of material growth have opposite effects on the background carrier concentration and carrier mobility.

Loop closure detection (LCD) is essential in the field of visual Simultaneous Localization and Mapping (vSLAM). In the LCD system, geometrical verification based on image matching plays a crucial role in avoiding erroneous detections. This paper focuses on adopting patch-level local features for image matching to compute the similarity score between the current query image and the candidate images. However, an important factor that may reduce the robustness is that some distracting and dynamic regions in a scene (e.g., the sky, cars, pedestrians, the ground, etc.) are not helpful and may seriously harm the performance. To address this challenge, we first use a newly designed patch descriptor loss to optimize the distance relationship between the patch-level local features. In this way, the patch-level local features extracted from the query/candidate images are more suitable for performing image matching. Moreover, we mimic the visual attention mechanism and propose a patch matching with saliency strategy, which enables local patches in salient regions to play crucial roles in image matching by assigning suitable weights to them. Finally, experiments on several public datasets demonstrate that the proposed LCD system can achieve encouraging improvements over the state-of-the-art approaches regarding recall rates under 100% precision.

High-temperature laser bed powder fusion (HT-LPBF) technology is an ideal method for processing poly-ether-ether-ketone (PEEK) implants with personalized bionic structures, but the biological inertia of PEEK limits its medical applications. In this study, we evaluated the mechanical and biological properties of a novel akermanite (AKM)/PEEK composite for HT-LPBF. The results showed that tiny AKM particles are evenly attached to the surface of the PEEK particle. The delayed peak crystallization temperature and stable sintering window ensure the processing feasibility of the AKM/PEEK composites. The tensile strength and Young's modulus are in the range of 30.83-98.73 MPa and 2.27-3.71 GPa, respectively, which can match the properties of cancellous bones and meet their implanting requirement. The CCK-8 experiments demonstrated the biocompatibility of the composites and the good proliferation of bone marrow stromal cells. The dense hydroxyapatite network layer and petal-like hydroxyapatite demonstrates biological activity, indicating that the composite has a good potential in the orthopedics fields.

Cyanobacteria have evolved since the early history of the Earth and played a critical role in Earth’s carbon cycle. However, the contribution of cyanobacteria to organic carbon burial has rarely been underscored due to their lack of lipids membrane, which are refractory materials ready for preservation in sediments. To clarify the role of cyanobacteria in organic carbon burial, we focus on kerogen, which is the precursor of petroleum and also one of the most important organic carbon pools. We first review the physiological and environmental characteristics of modern cyanobacteria, which sets the theoretical foundations for kerogen formation. Cyanobacteria cell wall contains refractory algaenan, biomacromolecules rich in long-chain aliphatic structures, which are ready to be preserved in sediments and generate hydrocarbons during pyrolysis. Cyanobacteria can also form dense blooms in special environments, such as high temperatures with limited nitrogen supply. We then compile the cyanobacteria-dominant kerogen to reveal its temporal distribution in geological history. The cyanobacteria-dominant kerogen is identified mainly by three criteria including high total organic carbon, high hopane/sterane ratio, and high 2-MeHop index. The results show that the biological parent material of Proterozoic kerogen is dominated by cyanobacteria when eukaryotic algae did not experience massive blooms. In Phanerozoic, cyanobacteria-dominant kerogen is formed in episodic ocean anoxic conditions, where strong denitrification reduced nitrogen supply and hindered the growth of eukaryotic algae. Rock-Eval results show that cyanobacteria-dominant kerogen could have higher hydrogen content than cyanobacteria algaenan. In addition, we compare two Proterozoic cyanobacteria-dominant black shales deposited in anoxic and partially oxic environments and find that the kerogen formed in the anoxic environment has much higher hydrocarbon potential than that formed in the oxic environment. The difference in hydrocarbon potential, together with kerogen compositions, indicates that decomposable molecules with higher hydrocarbon potential could also form kerogen besides refractory algaenan. Based on this holistic review, we propose a model for cyanobacteria flourishing and organic matter preservation and highlight the critical role cyanobacteria played in organic carbon burial in Earth's history.

Most visual recognition studies rely heavily on crowd-labelled data in deep neural networks (DNNs) training, and they usually train a DNN for each single visual recognition task, leading to a laborious and time-consuming visual recognition paradigm. To address the two challenges, Vision-Language Models (VLMs) have been intensively investigated recently, which learns rich vision-language correlation from web-scale image-text pairs that are almost infinitely available on the Internet and enables zero-shot predictions on various visual recognition tasks with a single VLM. This paper provides a systematic review of visual language models for various visual recognition tasks, including: (1) the background that introduces the development of visual recognition paradigms; (2) the foundations of VLM that summarize the widely-adopted network architectures, pre-training objectives, and downstream tasks; (3) the widely-adopted datasets in VLM pre-training and evaluations; (4) the review and categorization of existing VLM pre-training methods, VLM transfer learning methods, and VLM knowledge distillation methods; (5) the benchmarking, analysis and discussion of the reviewed methods; (6) several research challenges and potential research directions that could be pursued in the future VLM studies for visual recognition. A project associated with this survey has been created at https://github.com/jingyi0000/VLM_survey.

Background The immune microenvironment plays a critical role in maintaining skin homeostasis, which is closely related to the dysfunction in photoaged skin such as autoimmunity and tumorigenesis. Several recent studies have demonstrated the efficacy of 5-aminolevulinic acid photodynamic therapy (ALA-PDT) in alleviating photoaging and skin cancer. However, the underlying immune mechanisms and the immune microenvironment change by ALA-PDT remain largely unknown. Methods To illustrate the effects of ALA-PDT on immune microenvironment in photoaged skin, single cell RNA sequencing (scRNA-seq) analysis of photoaged skin on the extensor side of the human forearm before and after ALA-PDT was performed. R-packages of Seurat, clusterProfiler, Monocle, CellChat were used for cell clustering, differentially expressed genes analysis, functional annotation, pseudotime analysis and cell-cell communication analysis. The gene sets related to specific functions were extracted from the MSigDB database, which were used to score the functions of immune cells in different states. We also compared our result with published scRNA-seq data of photoaged skin of the eyelids. Results The increase score of cellular senescence, hypoxia and reactive oxygen species pathway in immune cells and the decrease of immune receptor activity function and proportion of naive T cells were found in skin photoaging. Moreover, the function of T cell ribosomal synthesis was also impaired or down regulated and function of G2M checkpoint was up regulated. However, ALA-PDT showed promising results in reversing these effects, as it improved the above functions of T cells. The ratio of M1/M2 and percentage of Langerhans cells also decreased with photoaging and increased after ALA-PDT. Additionally, ALA-PDT restored the antigen presentation and migration function of dendritic cells and enhanced cell-cell communication among immune cells. These effects were observed to last for 6 months. Conclusion ALA-PDT has potential to rejuvenate immune cells, partially reversed immunosenescence and improved the immunosuppressive state, ultimately remodelling the immune microenvironment in photoaged skin. These results provide an important immunological basis for further exploring strategies to reverse skin photoaging, chronological aging and potentially systemic aging.

Pre-trained vision-language models (VLMs) learn to align vision and language representations on large-scale datasets, where each image-text pair usually contains a bag of semantic concepts. However, existing open-vocabulary object detectors only align region embeddings individually with the corresponding features extracted from the VLMs. Such a design leaves the compositional structure of semantic concepts in a scene under-exploited, although the structure may be implicitly learned by the VLMs. In this work, we propose to align the embedding of bag of regions beyond individual regions. The proposed method groups contextually interrelated regions as a bag. The embeddings of regions in a bag are treated as embeddings of words in a sentence, and they are sent to the text encoder of a VLM to obtain the bag-of-regions embedding, which is learned to be aligned to the corresponding features extracted by a frozen VLM. Applied to the commonly used Faster R-CNN, our approach surpasses the previous best results by 4.6 box AP <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">50</inf> and 2.8 mask AP on novel categories of open-vocabulary COCO and LVIS benchmarks, respectively. Code and models are available at https://github.com/wusize/ovdet.

The Cu–Ge binary system was assessed thermodynamically using the CALPHAD method through Thermo-calc® software package based on the evaluation of all available experimental data from the published literature. The solution phases, including liquid, fcc, hcp and diamond (Ge), were described by the substitutional solution model, of which the excess Gibbs energies were expressed with the Redlich–Kister polynomial. Due to their narrow homogeneity ranges, all intermetallic compounds, ɛ-Cu0.765Ge0.235, θ-Cu0.735Ge0.265 and η-Cu0.75Ge0.25, were modeled as stoichiometric compounds. A set of self-consistent thermodynamic parameters formulating the Gibbs energies of various phases in the Cu–Ge binary system was obtained finally. A good agreement is achieved between the calculated results and the reported experimental data.

A 2.25$\times10^8$ $\jpsi$ event sample accumulated with the BESIII detector is used to study the doubly OZI suppressed decay modes $\jpsi\toγ\of$, $ω\to\ppp$, $ϕ\to\kk$. A strong deviation ($&gt;$ 30$σ$) from three-body $\jpsi\toγωϕ$ phase space is observed near the $ωϕ$ mass threshold that is consistent with a previous observation reported by the BESII experiment. A partial wave analysis with a tensor covariant amplitude that assumes that the enhancement is due to the presence of a resonance, the X(1810), is performed, and confirms that the spin-parity of the X(1810) is $0^{++}$. The mass and width of the X(1810) are determined to be $M=1795\pm7$(stat)$^{+13}_{-5}$(syst)$\pm$19(mod) MeV/$c^2$ and $Γ=95\pm10$(stat)$^{+21}_{-34}$(syst)$\pm$75(mod) MeV/$c^2$, respectively, and the product branching fraction is measured to be ${\cal B}(\jpsi\toγX(1810))\times{\cal B}(X(1810)\to\of)=(2.00\pm0.08$(stat)$^{+0.45}_{-1.00}$(syst)$\pm$1.30(mod))$\times10^{-4}$. %where the first error is the statistical error and the second the systematical error. These results are consistent within errors with those of the BESII experiment.

The impact of gender on clinical course after ST-elevation myocardial infarction (STEMI) is not fully understood. We prospectively investigated whether there are gender-related differences in epicardial and myocardial tissue-level perfusion, both of which represent important prognostic determinants in STEMI patients undergoing primary percutaneous coronary intervention (PPCI).A total of 594 consecutive non-selected STEMI patients undergoing PPCI were prospectively enrolled. Primary end-point of the study was post-procedural epicardial and myocardial perfusion. Secondary end-points were the 30-day and 6-month composite occurrence of major adverse cardiac events (MACE).Women with STEMI had higher risk factor profiles than men. Although PPCI achieved equal rates of successful epicardial reperfusion, women tended to have impaired microvascular reperfusion as reflected by lower rates of normal TIMI myocardial perfusion grade (P=0.007) and complete ST-segment resolution (P=0.079). After adjustment for the risk profiles, multivariable analysis showed that gender itself was not an independent predictor of impaired microvascular reperfusion. Both female gender and impaired myocardial reperfusion were independent predictors of 30-day MACE, whereas gender lost its prognostic significance for 6-month MACE. Multivariable analysis restricted to female patients identified incomplete ST-segment resolution as the strongest determinant of 30-day MACE.The differences in microvascular reperfusion after PPCI between women and men are attributed to higher risk profiles in women. Both female gender and impaired myocardial reperfusion were independent predictors of 30-day outcomes after PPCI, emphasizing the importance of successful microvascular reperfusion in the women with STEMI.

The enthalpies of formation of the intermetallic compounds in the Ge-Ni binary system have been determined by calorimetric measurement and first-principles calculations. Based on the results obtained and information available in the literature, the phase diagram and thermodynamic properties of the Ge-Ni system have been re-assessed using the CALPHAD approach [L. Kaufman, H. Bernstein, Computer Calculation of Phase Diagrams, Academic Press, New York (1970)], applying appropriate thermodynamic models for the phases. The liquid phase and the Ni-based solid solution (Ni) were modeled as substitutional solutions using the Redlich-Kister equation to represent the excess Gibbs energy. The B8-type intermediate phases εNi5Ge3, Ni19Ge12 and Ni3Ge2 were treated as a single phase, designated as Ni5Ge3. A three-sublattice model with stoichiometry (Ge)(Ni)(Va,Ni) was used to describe the B8-type Ni5Ge3-phase based on its crystal structure. The order-disorder transformation between disordered FCC_A1 and the ordered L12-type phase, βNi3Ge, was treated using a two-sublattice model. The other five intermetallic compounds were treated as stoichiometric compounds. The phase diagram and the thermodynamic properties calculated from the optimized model parameters are in good agreement with most of the experimental data.

Cardiac telerehabilitation is a method that uses digital technologies to deliver cardiac rehabilitation from a distance. It has been shown to have benefits to improve patients' disease outcomes and quality of life, and further reduce readmission and adverse cardiac events. The outbreak of the coronavirus pandemic has brought considerable new challenges to cardiac rehabilitation, which foster cardiac telerehabilitation to be broadly applied. This transformation is associated with some difficulties that urgently need some innovations to search for the right path. Artificial intelligence, which has a high level of data mining and interpretation, may provide a potential solution. This review evaluates the current application and limitations of artificial intelligence in cardiac telerehabilitation and offers prospects.

Atherosclerotic cardiovascular diseases remain the leading causes of morbidity and mortality worldwide. Cholesterol crystals in atherosclerotic plaques play an essential role in atherosclerosis progression. However, no clinical drugs have been used for removing cholesterol crystals from plaque to counter atherosclerosis. Previous studies identified the hydrophobic domain of lipid bilayer in liposomes acted as sinks for solubilizing hydrophobic cholesterol. Moreover, adjusting the composition of the lipid bilayer in liposomes can enhance its hydrophobic molecule loading capacity. Therefore, in this study, ginsenosides Rb1 (Rb1), one of main active components of ginseng which has a similar structure to cholesterol, is anchored into soy phospholipids bilayer with its hydrophobic region to prepare nano-sponge-like liposomes (Rb1-LPs), aiming to amplify the solubilization of cholesterol in lipid bilayer. For targeting delivery to atherosclerotic plaques, Annexin V (AnxV), a protein that can specifically recognize phosphatidylserine upregulated in atherosclerotic plaques, is applied to decorate the surface of Rb1-LPs by click reaction to obtain the final preparation of AnxV-Rb1-LPs. The in vitro studies showed that incorporating Rb1 into lipid bilayer remarkably increased the affinity of the lipid bilayer to free cholesterol and the solubilization of cholesterol crystals. Additionally, nano-sponge-like liposomes could efficiently reduce the accumulation of cholesterol crystals and improve cholesterol efflux, finally inhibiting inflammation and apoptosis in cholesterol-laden cells. Furthermore, AnxV-Rb1-LPs could efficiently accumulate in atherosclerotic plaques after intravenous injection, exert nano-sponge-like functions to remove intra- and extracellular cholesterol crystals, ultimately alleviating inflammation and apoptosis in atherosclerotic plaques for antiatherosclerosis. Therefore, AnxV-Rb1-LPs provide a potential strategy for removing cholesterol crystals in atherosclerotic plaques and can be further utilized in other diseases with excessive cholesterol accumulation.

We report a numerical and theoretical study of the generation and propogation of oscillations in the semiclassical limit (h → 0) of the Nonlinear Schrödinger equation. In a general setting of both dimension and nonlinearity, we identify essential differences between the “defocusing” and “focusing” cases. Numerical comparisons of the oscillations are made between the linear (“free”) and the cubic (defocusing and focusing) cases in one dimension. The integrability of the one-dimensional cubic NLS is exploited to give a complete global characterization of the weak limits of the oscillations in the defocusing case.

We report measurements of the line shapes of D+D−, D0D¯0 and DD¯ production as well as the line shape of the ratio of the production rates of D+D− and D0D¯0 in e+e− annihilation at ψ(3770) resonance. We find that the line shapes of D+D−, D0D¯0 and DD¯ production are similar to an anomalous line shape of cross sections for e+e−→hadrons observed in the center-of-mass energy range from 3.70 to 3.87 GeV.

Aquaculture ponds in Zaria, Nigeria, were screened for the occurrence of the hepatotoxic microcystins using an ELISA method.Four genera of cyanobacteria (Microcystis, Nostoc, Planktothrix and Anabaena) were recorded from 11 aquaculture ponds screened.These cyanobacteria are generally known to produce microcystins and other bioactive substances.Six of the 11 aquaculture ponds had detectable concentrations of microcystins (ranging from 0.6 to 5.89 µg/L).This means that there is the possibility of bioaccumulation of microcystins in fish.The implication of this is that people that feed on contaminated fish from these ponds stand the risk of microcystins poisoning.

Abstract Organ transplant patients are often treated with immunosuppressants, such as the calcineurin phosphatase inhibitor, cyclosporin A, to block T cell-mediated graft rejection. The calcium release-activated calcium (CRAC/ORAI) channels, which act upstream of calcineurin, are essential for calcium entry and CD4+ T-cell activation. Although cyclosporine A has also been shown to inhibit FoxP3+ Tregs both in vitro and in vivo, the role of ORAI channel inhibition in natural Tregs (nTregs) or inducible Tregs (iTregs) has not been investigated. We found that, despite inhibition of calcium influx through the ORAI channels, ORAI channel inhibitors were unable to repress FoxP3 expression in mouse and human nTregs, whereas FoxP3 expression was inhibited in iTregs. In contrast, cyclosporin A inhibited FoxP3 expression in both nTregs and iTregs. We also generated mice with a T cell-specific, conditional knockout of ORAI1 and found that the mice have normal nTreg development and suppressive activity. Moreover, iTregs derived from ORAI1 conditional knockout mice develop normally and are still susceptible to ORAI channel inhibition. Our data indicate that unlike CD4+ T cells and iTregs, nTregs are resistant to ORAI-mediated inhibition. Targeting ORAI channels potentially offers a novel way to inhibit pathologic T cells, while sparing nTreg-mediated tolerance.

As a means to share knowledge, the community question answering (CQA) service provides users a chance to obtain or provide help by raising or answering questions. After a question is posted, the system must find an appropriate individual to answer this question. Several approaches have recently been proposed to find experts in CQA. In this paper, a new method to find experts in CQA is proposed by considering user post contents, answer votes, ratio of best answers, and user relation. The votes are used in post relation analysis to calculate user authority. The user's knowledge score can be calculated through topic analysis. Considering that a question usually includes many trivial words, an accurate distribution is nearly impossible to obtain with LDA. To solve this problem, vocabulary is extended by including the link information shown in a question, the top 10 relevant words from Wikipedia are provided for each tag. Tag-LDA models the user topic distribution and predicts the topic distribution of new questions. An experiment is conducted on Stack Overflow dataset, which is the world's largest computer programming CQA site. Experimental results showed approximately 2.97% to 7.79% performance improvement in nDCG@N metrics.

Human reliability analysis (HRA) and optimization in manufacturing systems are effective to reduce system failure. The purpose of this study is to examine the HRA and optimization through a Bayesian network (BN) model and human factors experiments (HFEs). This study was applied to a flexible intermediate bulk container manufacturing plant. The human physiological and psychological factors consisting of personal abilities of flexibility, coordination, memory, and attention were regarded as the only performance shaping factors in this study. With the BN model, the relationship between human factors and human errors was described qualitatively and the impact of the human factor on system failures was judged quantitatively. Then the workers’ abilities training with HFEs based on the fault diagnosis results was carried out. The total numbers of errors have been decreased by 69.06% and the system failure rate has been reduced significantly after training.

The application of deep learning is blooming in the field of visual place recognition, which plays a critical role in visual Simultaneous Localization and Mapping (vSLAM) applications. The use of convolutional neural networks (CNNs) achieve better performance than handcrafted feature descriptors. However, visual place recognition is still a challenging task due to two major problems, i.e., perceptual aliasing and perceptual variability. Therefore, designing a customized distance learning method to express the intrinsic distance constraints in the large-scale vSLAM scenarios is of great importance. Traditional deep distance learning methods usually use the triplet loss which requires the mining of anchor images. This may, however, result in very tedious inefficient training and anomalous distance relationships. In this paper, a novel deep distance learning framework for visual place recognition is proposed. Through in-depth analysis of the multiple constraints of the distance relationship in the visual place recognition problem, the multi-constraint loss function is proposed to optimize the distance constraint relationships in the Euclidean space. The new framework can support any kind of CNN such as AlexNet, VGGNet and other user-defined networks to extract more distinguishing features. We have compared the results with the traditional deep distance learning method, and the results show that the proposed method can improve the performance by 19–28%. Additionally, compared to some contemporary visual place recognition techniques, the proposed method can improve the performance by 40%/36% and 27%/24% in average on VGGNet/AlexNet using the New College and the TUM datasets, respectively. It’s verified the method is capable to handle appearance changes in complex environments.

Abstract Hadron spectroscopy provides a way to understand the dynamics of the strong interaction. For light hadron systems, only phenomenological models or lattice quantum chromodynamics (QCD) are applicable, because of the failure of perturbation expansions for QCD at low energy. Experimental data on light hadron spectroscopy are therefore crucial to provide necessary constraints on various theoretical models. Light meson spectroscopy has been studied using charmonium decays with the Beijing Spectrometer Experiment (BES) at the Beijing Electron-Positron Collider, operating at 2.0–4.6 GeV center-of-mass energy, for nearly three decades. Charmonium data with unprecedented statistics and well-defined initial and final states provide BESIII with unique opportunities to search for glueballs, hybrids and multi-quark states, as well as perform systematic studies of the properties of conventional light mesons. In this article, we review BESIII results that address these issues.

Features play an important role in achieving robust visual simultaneous localization and mapping (SLAM) in complex environments. Although all scene features provide a certain amount of information, their importance to SLAM is different. Similar to the human attention mechanism, close attention should be paid to features in salient and important regions. Therefore, this paper proposes a saliency prediction-based SLAM (SP-SLAM), which represents a visual SLAM system that combines the ORB-SLAM3 with a saliency prediction model. The proposed combined saliency prediction model focuses on the right regions by considering geometric, semantic, and depth information, thus making visual SLAM more accurate. Moreover, a multi-level strategy is introduced to make the saliency prediction model continuously focus on the same regions, which can learn the temporally consistent information between adjacent images. Then, the predicted saliency map is used to provide salient weights for robust tracking and optimization to improve the accuracy of visual SLAM. Finally, comprehensive test results show that the proposed SP-SLAM has superior performance in terms of localization accuracy and saliency prediction performance.

The disease burden of coronary heart disease patients in Tibet, China, ranks high in the country. Due to the local culture and environment, patients with coronary heart disease have increased risk factors for the disease, and their survival is worrisome.The purpose of this study was to determine the relationship between health literacy and quality of life for patients with coronary heart disease in Tibet, China, and to explore the mediating roles of self-efficacy and self-management.A cross-sectional study was conducted from August 2020 to July 2021 in Tibet. A total of 258 patients with coronary heart disease in Tibet participated. Self-reported questionnaires were used to assess health literacy, self-efficacy, self-management, and quality of life. Pearson correlation analysis and the SPSS PROCESS macro were used to analyze the data.The mean total score for the health literacy of patients with coronary heart disease in Tibet was 3.59 ± 0.80 points, showing the existence of a limited level of literacy. The quality of life was of an average level, with scores of 57.20 ± 21.70 points and 63.63 ± 20.66 points for physical and mental status, respectively. Self-efficacy and self-management mediated the relationship between health literacy and quality of life.Self-efficacy and self-management mediate the relationship between health literacy and quality of life. Targeted interventions for health literacy, self-efficacy, and self-management skills are important to improve the quality of life of Tibetan patients with coronary heart disease.

You have accessJournal of UrologyCME1 Apr 2023LBA02-03 FIRST RESULTS FROM SunRISE-1 IN PATIENTS WITH BCG UNRESPONSIVE HIGH-RISK NON–MUSCLE-INVASIVE BLADDER CANCER RECEIVING TAR-200 IN COMBINATION WITH CETRELIMAB, TAR-200, OR CETRELIMAB ALONE Siamak Daneshmand, Michiel S van der Heijden, Joseph M Jacob, Andrea Necchi, Evanguelos Xylinas, David S Morris, Philip Spiegelhalder, Daniel Zainfeld, Taek Won Kang, Justin T Matulay, Laurence H Belkoff, Karel Decaestecker, Harm Arentsen, Shalaka Hampras, Shu Jin, Christopher J Cutie, Hussein Sweiti, Katherine Stromberg, Jason Martin, and Giuseppe Simone Siamak DaneshmandSiamak Daneshmand More articles by this author , Michiel S van der HeijdenMichiel S van der Heijden More articles by this author , Joseph M JacobJoseph M Jacob More articles by this author , Andrea NecchiAndrea Necchi More articles by this author , Evanguelos XylinasEvanguelos Xylinas More articles by this author , David S MorrisDavid S Morris More articles by this author , Philip SpiegelhalderPhilip Spiegelhalder More articles by this author , Daniel ZainfeldDaniel Zainfeld More articles by this author , Taek Won KangTaek Won Kang More articles by this author , Justin T MatulayJustin T Matulay More articles by this author , Laurence H BelkoffLaurence H Belkoff More articles by this author , Karel DecaesteckerKarel Decaestecker More articles by this author , Harm ArentsenHarm Arentsen More articles by this author , Shalaka HamprasShalaka Hampras More articles by this author , Shu JinShu Jin More articles by this author , Christopher J CutieChristopher J Cutie More articles by this author , Hussein SweitiHussein Sweiti More articles by this author , Katherine StrombergKatherine Stromberg More articles by this author , Jason MartinJason Martin More articles by this author , and Giuseppe SimoneGiuseppe Simone More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003361.03AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Patients (pts) with high-risk non–muscle-invasive bladder cancer (HR NMIBC) unresponsive to intravesical BCG have limited treatment (tx) options. TAR-200 is a novel intravesical drug delivery system that provides sustained local release of gemcitabine into the bladder. Cetrelimab (CET) is an anti-PD1 agent. SunRISe-1 is an ongoing ph 2 study evaluating efficacy and safety of TAR-200 + CET (Cohort 1 [C1]), TAR-200 alone (C2), or CET alone (C3) in BCG-unresponsive pts with HR NMIBC (carcinoma in situ [CIS]) who are ineligible for or decline radical cystectomy. We report preliminary results from SunRISe-1, providing data from C2 and C3. METHODS: Pts ≥18 y with histologically confirmed CIS±papillary disease (T1, high-grade Ta) who completed adequate BCG ≤12 mo before enrollment and with ECOG performance status 0-2 were randomized to C1, C2, or C3. TAR-200 was dosed Q3W through Wk 24, then Q12W until Wk 96. CET was dosed through Wk 78. Cystoscopy, centrally read urine cytology, CT/MRI, and TURBT (bladder biopsy) were done at baseline and prespecified time points to assess disease response. The primary end point is overall complete response (CR) rate at any time point. Secondary end points include duration of response (DOR), overall survival, PK, quality of life, safety, and tolerability. Initial results are reported; updated data (≈40 pts) will be included in the presentation. RESULTS: As of data cutoff (May 25, 2022), 13 pts in C2 and 13 in C3 (median 71.5 y [range 51-88]) received tx. Efficacy evaluable set: 8 pts in C2, 8 in C3. Centrally confirmed CR by urine cytology and/or biopsy was 88% (95% CI 47-100) in C2 and 38% (9-76) in C3. Median CR duration of response for C2 and C3 was not reached after median follow-up of 13.6 and 12.0 wks, respectively. At data cutoff, 7 of 8 pts in C2 remained CR, with 3 ongoing responses ≥6 mo (range 7.7-9.4 mo). 11 pts (85%) in C2 and 8 (62%) in C3 had tx-emergent adverse events (TEAEs); most were Gr 1-2. The most common TEAEs were pollakiuria (39%), micturition urgency (39%), and noninfective cystitis (39%) in C2; fatigue (23%) and lipase increased (23%) in C3. 1 pt (8%) in C2 and 2 pts (15%) in C3 had tx-related Gr ≥3 TEAEs. 1 serious TEAE (myocarditis) occurred in C3. CONCLUSIONS: First results from SunRISe-1 show promising CR rate and safety profile with TAR-200 monotherapy, and CET results are consistent with other anti-PD(L)1 tx in this setting. Preliminary efficacy and safety data support the continued study in NMIBC. Source of Funding: Janssen Research & Development © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e1187 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Siamak Daneshmand More articles by this author Michiel S van der Heijden More articles by this author Joseph M Jacob More articles by this author Andrea Necchi More articles by this author Evanguelos Xylinas More articles by this author David S Morris More articles by this author Philip Spiegelhalder More articles by this author Daniel Zainfeld More articles by this author Taek Won Kang More articles by this author Justin T Matulay More articles by this author Laurence H Belkoff More articles by this author Karel Decaestecker More articles by this author Harm Arentsen More articles by this author Shalaka Hampras More articles by this author Shu Jin More articles by this author Christopher J Cutie More articles by this author Hussein Sweiti More articles by this author Katherine Stromberg More articles by this author Jason Martin More articles by this author Giuseppe Simone More articles by this author Expand All Advertisement PDF downloadLoading ...

Solid-state electrolytes (SSEs) are a frontier topic in battery technology with the potential to solve the safety problem of lithium ion batteries (LIBs). Metal organic frameworks (MOFs) are regarded as promising candidates for a new type of solid-state ion conductor, but the low ionic conductivity and unstable interface contact still seriously hinder the application of MOF based solid state electrolytes (SSEs). Herein, a HKUST-1 based solid-state electrolyte (SSE) was designed and prepared, which possess both a flower-like lamellar structure and sufficient accessible open metal sites (OMSs). These sites could capture anions and release free lithium ions (Li+), and the ultra-thin thickness shortened the Li+ transmission path. The lamellar HKUST-1 exhibits an ionic conductivity of 1.6 × 10-3 S cm-1 at 25 °C with an activation energy of 0.12 eV, Li-ion transference number of 0.73 and electrochemical stability window of 0-5.5 V. The MOF based electrolyte has been assessed with Li|MOFs|LiFePO4 cells at 25 °C, which showed a high capacity retention of 93% at 0.1C after 100 cycles and excellent rate capability. It also exhibited excellent cycle stability in Li symmetric cells. This Li+ conduction strategy of modulating the morphology and modifying pore walls provides a new research idea for designing advanced SSEs.

Abstract Background Nutrition service needs are huge in China. Previous studies indicated that personalized nutrition (PN) interventions were effective. The aim of the present study is to identify the effectiveness and feasibility of a novel PN approach supported by artificial intelligence (AI). Methods This study is a two-arm parallel, randomized, controlled trial in real world scenario. The participants will be enrolled among who consume lunch at a staff canteen. In Phase I, a total of 170 eligible participants will be assigned to either intervention or control group on 1:1 ratio. The intervention group will be instructed to use the smartphone applet to record their lunches and reach the real-time AI-based information of dish nutrition evaluation and PN evaluation after meal consumption for 3 months. The control group will receive no nutrition information but be asked to record their lunches though the applet. Dietary pattern, body weight or blood pressure optimizing is expected after the intervention. In phase II, the applet will be free to all the diners (about 800) at the study canteen for another one year. Who use the applet at least 2 days per week will be regarded as the intervention group while the others will be the control group. Body metabolism normalization is expected after this period. Generalized linear mixed models will be used to identify the dietary, anthropometric and metabolic changes. Discussion This novel approach will provide real-time AI-based dish nutrition evaluation and PN evaluation after meal consumption in order to assist users with nutrition information to make wise food choice. This study is designed under a real-life scenario which facilitates translating the trial intervention into real-world practice. Trial registration This trial has been registered with the Chinese Clinical Trial Registry (ChiCTR2100051771; date registered: 03/10/2021).

Self-supervised monocular depth estimation has attracted extensive attention in recent years. Lightweight depth estimation methods are crucial for resource-constrained edge devices. However, existing lightweight methods often encounter the challenge of limited representation capacity and increased computational resource consumption for image reconstruction. To alleviate these issues, we propose a novel spatial-aware dynamic lightweight monocular depth estimation method (SAD-Depth). Specifically, we propose a spatial-aware dynamic encoder, which can capture spatial information of the input and generate input-adaptive dynamic convolutions, thereby significantly enhancing the model's adaptability to complex scenes. Meanwhile, we propose a multi-scale sub-pixel lightweight decoder that generates high-quality depth maps while maintaining a lightweight design. Experimental results demonstrate that our proposed SAD-Depth exhibits superiority in both model size and inference speed, achieving state-of-the-art performance on the KITTI benchmark.

Randomness and non-stationarity are common challenges in wind power forecasting (WPF). Many studies focus on randomness but usually ignore the non-stationarity which leads to distribution shift and affects prediction accuracy. To address the distribution shift problem, an alleviating distribution shift using the recent difference characterization (Dish-RDC) method is proposed as a general neural paradigm for WPF. Dish-RDC categorizes the distribution shift into intra-space and inter-space shifts. By employing the RDC, the method facilitates the mapping of input sequences to learnable distribution coefficients that better estimate the distribution. Furthermore, real-world time series often exhibit multi-periodicity, yet existing models face limitations in capturing this temporal variation. To address this issue, our research introduces the Temporal 2D-Variation Model (TimesNet) in WPF. This innovative model extends time variation analysis into a 2D space based on multi-periodicity. By using 2D kernels to model these variations, TimesNet can effectively incorporate advanced computer vision techniques into WPF. Combining these approaches, we developed Dish-RDC-TimesNet, a hybrid model. Experiments show it reduced mean absolute error (MAE) by 47.10 % and 20.63 % on two datasets compared to benchmark models. Moreover, integrating Dish-RDC with benchmark models decreased MAE by 39.79 % and 17.85 % on these datasets.

Visual navigation in unknown environments poses significant challenges due to the presence of many obstacles and low-texture scenes. These factors may cause frequent collisions and tracking failure of feature-based visual Simultaneous Localization and Mapping (vSLAM). To avoid these issues, this paper proposes a spatial memory-augmented visual navigation system that combines a vSLAM module, a conventional global planner module, and a Hierarchical Reinforcement Learning (HRL)-based local planner module. Firstly, a real-time vSLAM named Salient-SLAM is proposed to augment the performance of visual navigation. Salient-SLAM creates a navigation mapping thread by combining a saliency prediction model to build a navigation map that categorizes environmental regions as occupied, explored, or noticeable. Spatial memory that contains spatial abstraction and saliency information of the environment can be further formed by encoding navigation maps, which helps the agent determine an optimal path towards its destination. An open-sourced saliency dataset is proposed to train the saliency prediction model by mimicking the visual attention mechanism. Secondly, a HRL method is proposed to automatically decompose local planning into a high-level policy selector and several low-level policies, where the latter produces actions to interact with the environment. We maximize entropy and minimize option correlation in learning low-level policies, aiming at acquiring diverse and independent behaviors. The simulation results show that the proposed HRL method outperforms competitive baselines by 6.29–10.85 % on Success Rate (SR) and 3.87–11.1 % on Success weighted by Path Length (SPL) metrics. By incorporating the spatial memory, SR, and SPL metrics can be augmented by an average of 9.85 % and 10.89 %, respectively.

Europe faces an elevated risk of nonalcoholic fatty liver disease (NAFLD) among people living with HIV (PLWH), contributing to the region's highest global burden of NAFLD. However, the prevalence of NAFLD across various European countries and regions remains unclear. This study aims to investigate the prevalence and risk factors associated with NAFLD among PLWH across European countries.A systematic search was conducted across four databases: PubMed, Embase, Web of Science, and Cochrane Library. Data on the prevalence of NAFLD, nonalcoholic steatohepatitis (NASH), and fibrosis, as well as the associated risk factors, were collected among PLWH in Europe.Thirty-six studies from 13 European nations were included. The prevalence of NAFLD, NASH, and fibrosis were 42% (95%CI 37-48), 35% (95%CI 21-50) and 13% (95%CI 10-15), respectively. Male gender, BMI, waist circumference, Diabetes, hypertension, metabolic syndrome, dyslipidemia, triglycerides, HDL, LDL, ALT, AST, and years on antiretroviral therapy (ART) were found to be risk factors for NAFLD. High BMI and triglycerides were associated with NASH. Patients with high BMI and triglycerides are at increased risk of significant liver fibrosis.The high prevalence of NAFLD, NASH, and fibrosis among PLWH in Europe highlights the need for early screening, intervention, and increased research focus on adolescents living with HIV. Furthermore, the significant variations observed between countries and regions underscore the influence of related risk factors.

Abstract In the actual operation of a 300 MW boiler, there are some problems such as unstable combustion, high combustible material of fly ash and slag, and large thermal deviation on both sides of steam. The Cooper method is used to divide the three parts of the furnace by a hexahedral structured grid, which can reduce the grid number and improve the numerical simulation calculation precision. The Realization k-ε turbulent model is used to simulate the gas-solid two-phase flow in the furnace before and after reconstruction. The boundary of the calculation model adopts the actual operating parameters, and the numerical calculation adopts the three-dimensional steady-state calculation - Simple algorithm. The conclusions are as follows: the amount of pulverized coal powder falling into the cold ash hopper is reduced from 0.077 kg/m 3 before the reconstruction to 0.045 kg/m 3 after the reconstruction, with a decrease of about 42%. The secondary air concentration arrangement in the lowest two layers strengthened the secondary air supporting capacity. The residence time of pulverized coal particles in the furnace is increased from 30.59 s before the reconstruction to 39.97 s after the reconstruction, and the time is extended by about 9.4 s, which is beneficial to the combustion of pulverized coal particles. The centralized arrangement of primary air in the lowest two layers is beneficial to the initial ignition and stable combustion of pulverized coal gas. The downdip of the tertiary air incidence angle reduces the rotational momentum of the tertiary airflow, and the increase of the rotational momentum of the over-fire air angle is conducive to weakening the residual rotation at the furnace outlet. After the implementation of the reconstruction measures, the boiler can be stably burned at 150 MW, the combustible material of fly ash and slag are reduced to the controllable range, the steam thermal deviation is significantly reduced, and the boiler operating parameters are stable.

In the trirhythmic system, the coexistence of three stable limit cycles(LCs) renders the system highly sensitive to subtle input variations. This study meticulously examines how system parameters, filtered feedback control, and Gaussian perturbations impact the system's bifurcation behaviors. Using the harmonic decomposition method, the deterministic bifurcation behaviors of the trirhythmic system under filtered feedback control are explored. By applying the stochastic averaging method, the stationary probability density function(SPDF) of the system's amplitude is derived, further facilitating the construction of one-parameter and two-parameter bifurcation diagrams. These diagrams contribute to a thorough understanding of the multirhythmic oscillation phenomenon within the system. It should be noted that the presence of noise with higher intensity significantly disrupts the rhythmicity of the system, while the introduction of filtered feedback control ensures multirhythmic oscillation to a large extent. Furthermore, the magnitudes of parameters $\alpha$ and $\beta$ profoundly influence the amplitude distribution range: larger values correspond to narrower amplitude distribution ranges, whereas smaller values result in broader distributions. The proposed method in this paper exhibits high precision, and numerical results validate the accuracy of the theoretical analysis.

Measuring accurate concentration levels of potentially toxic elements in agricultural soils is necessary to prevent hazards to human health. X-ray fluorescence spectroscopy (XRF) allows rapid, non-destructive detection of potentially toxic...

Inspired by the outstanding zero-shot capability of vision language models (VLMs) in image classification tasks, open-vocabulary object detection has attracted increasing interest by distilling the broad VLM knowledge into detector training. However, most existing open-vocabulary detectors learn by aligning region embeddings with categorical labels (e.g., bicycle) only, disregarding the capability of VLMs on aligning visual embeddings with fine-grained text description of object parts (e.g., pedals and bells). This paper presents DVDet, a Descriptor-Enhanced Open Vocabulary Detector that introduces conditional context prompts and hierarchical textual descriptors that enable precise region-text alignment as well as open-vocabulary detection training in general. Specifically, the conditional context prompt transforms regional embeddings into image-like representations that can be directly integrated into general open vocabulary detection training. In addition, we introduce large language models as an interactive and implicit knowledge repository which enables iterative mining and refining visually oriented textual descriptors for precise region-text alignment. Extensive experiments over multiple large-scale benchmarks show that DVDet outperforms the state-of-the-art consistently by large margins.

Journal of Agricultural EconomicsVolume 75, Issue 1 p. 1-2 ISSUE INFORMATIONFree Access Issue Information First published: 09 February 2024 https://doi.org/10.1111/1477-9552.12552AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinkedInRedditWechat Volume75, Issue1February 2024Pages 1-2 RelatedInformation

The objective of this study was to assess the feasibility and effectiveness of a novel WeChat applet-based personalized dietary intervention aimed at promoting healthier dietary intakes. A two-arm parallel, randomized, controlled trial was conducted in a real-world scenario and involved a total of 153 participants (the intervention group, n = 76; the control group, n = 77), lasting for 4 months in Shanghai, China. The intervention group had access to visualized nutrition evaluations through the applet during workday lunch time, while the control group received no interventions. A total of 3413 lunch dietary intake records were captured through the applet. Linear mixed models were utilized to assess the intervention effects over time. At baseline, the participants’ lunchtime dietary intakes were characterized by insufficient consumption of plant foods (86.9% of the participants) and excessive intake of animal foods (79.7% of the participants). Following the commencement of the intervention, the intervention group showed a significant decrease in the animal/plant food ratio (β = −0.03/week, p = 0.024) and the consumption of livestock and poultry meat (β = −1.80 g/week, p = 0.035), as well as a borderline significant increase in the consumption of vegetables and fruits (β = 3.22 g/week, p = 0.055) and plant foods (β = 3.26 g/week, p = 0.057) over time at lunch compared to the control group. The applet-based personalized dietary intervention was feasible and effective in improving dietary intakes and, consequently, possibly may manage body weight issues in real-world scenarios.

One significant assessing criteria of climate change is geometric evolution. The rate of evolution reveals the speed that environment worsens. Advanced space mirror monitors that and generates images timely. However, it might be difficult for human to deal with collected numerous image-related data. In previous research, convolutional neural network is regarded to have specific advantage in resolving image recognition tasks. Hence, a new type of convolutional neural network model is applied to identify different kinds of landscape. Virtually, this model is called Efficient Net which based on landscape recognition dataset with 5 classes of landscapes. The study also introduces the fine-tuning to further improve the performance of the model. To evaluate the model, the precision, recall, F1 score, accuracy and loss are adopted as assessing criteria. The results shows that the model predicts the target dataset to a great extent. However, it has been tested that the class of mountain might not be suitable for predicting because of vague criterion. That is helpful in real-condition geographical applications and environmental governance.

Seipin deficiency is an important cause of type 2 Berardinelli-Seip congenital dyslipidemia (BSCL2). BSCL2 is a severe lipodystrophy syndrome with lack of adipose tissue, hepatic steatosis, insulin resistance, and normal or higher bone mineral density. Bone marrow mesenchymal stem cells (BMSCs) are believed to maintain bone and fat homeostasis by differentiating into osteoblasts and adipocytes. We aimed to explore the role of seipin in the osteogenic/adipogenic differentiation balance of BMSCs. Seipin loxP/loxP mice are used to explore metabolic disorders caused by seipin gene mutations. Compared with wild-type mice, subcutaneous fat deficiency and ectopic fat accumulation were higher in seipin knockout mice. Microcomputed tomography of the tibia revealed the increased bone content in seipin knockout mice. We generated seipin-deficient BMSCs in vitro and revealed that lipogenic genes are downregulated and osteogenic genes are upregulated in seipin-deficient BMSCs. In addition, peroxisome proliferator-activated receptor gamma (PPARγ) signaling is reduced in seipin-deficient BMSCs, while using the PPARγ activator increased the lipogenic differentiation and decreased osteogenic differentiation of seipin-deficient BMSCs. Our findings indicated that bone and lipid metabolism can be regulated by seipin through modulating the differentiation of mesenchymal stem cells. Thus, a new insight of seipin mutations in lipid metabolism disorders was revealed, providing a prospective strategy for MSC transplantation-based treatment of BSCL2.

Abstract Hydraulic fracturing, essential for shale reservoir exploitation, relies on wellhead pressure as a key indicator for monitoring and diagnosing fracturing stimulation. The strong heterogeneity of shale reservoirs complicates fracture propagation and proppant transport, leading to complex pressure fluctuations. Accurate modeling and prediction of wellhead pressure during hydraulic fracturing aid engineers in real-time monitoring and risk assessment, providing a basis for adjusting pumping parameters, ensuring a smooth completion of the fracturing plan, and successful production enhancement. Compared to purely data-driven models, we developed a wellhead pressure prediction model integrating deep learning and physical models, considering the actual physical processes of hydraulic fracturing. Appropriate neural network algorithms were selected for various scenarios of fracturing fluid flow, effectively modeling and predicting complex pressure fluctuations in the wellbore and formation fracture systems. The integrated model incorporates a physical model for hydrostatic pressure fluctuations and a parallel (MLP-LSTM) neural network for friction and net pressure changes. We collected over 1391 historical treatment curve datasets from the shale gas fracturing for training and testing. Compared to pure data-driven models, the data-physics integrated wellhead pressure prediction model captures future wellhead pressure trends(increases/decreases) triggered by changes in the pumping procedure and parameters more effectively through the inclusion of a physical model. The optimized data input and the introduction of a parallel neural network structure enable the integrated model to accurately model and learn net pressure fluctuations and friction changes within the formation fracture system, demonstrating the effectiveness of deep learning methods in modeling complex non-linear physical processes such as fracture propagation and proppant transport. The integrated model has been deployed and verified at 18 fracturing stages on the shale gas fracturing site in Wei Yuan, Sichuan Basin, and has successfully predicted rapid pressure increases, alerting field personnel to avoid fracturing screen-out risks 5 times. Based on field test data, the integrated model achieved a wellhead pressure prediction 90 seconds in advance with an RMSPE of 0.07993 and a MAPE of 0.078708. The integrated model accurately predicts pressure trends during treatment, enabling real-time monitoring and adjustment of proppant concentration and flow rate in the main fracturing stage, thereby enhancing fracturing completion rates and production. This research presents the data-physics-driven deep learning approach for wellhead pressure prediction during hydraulic fracturing. By integrating physical models, we enhance model reliability while leveraging deep learning's superior capabilities in learning and modeling complex physical processes. This allows for accurate, efficient wellhead pressure prediction during fracturing treatments, providing engineers with a basis for monitoring hydraulic fracturing, reducing operational complexity, and ensuring effective fracturing stimulation.

To investigate the predictive value of neutrophil-to-lymphocyte ratio (NLR) in the short-term prognosis of elderly patients with severe sepsis combined with diabetes mellitus (DM).The clinical data of 162 elderly patients with severe sepsis combined with DM from January 2018 to December 2022 were retrospectively collected. These patients were divided into a survival group (n = 104) and a death group (n = 58) according to 90-day prognosis. The number of neutrophils, lymphocytes, and NLR were compared. The optimal cut-off value for NLR to predict 90-day prognosis in elderly patients with severe sepsis combined with DM was determined using Receiver Operator Characteristic (ROC) curves, and the patients were divided into high and low NLR groups depending on the optimal cut-off value. The Kaplan-Meier method was used to plot the survival curves of the high and low NLR groups. Risk factors for the 90-day death in elderly patients with severe sepsis combined with DM were analyzed by a multivariate cox regression model.There were no significant differences in gender, age, history of hypertension and hyperlipidemia, intensive care unit (ICU) stay, duration of mechanical ventilation, and oxygenation index between the survival group and death group (p > 0.05). However, acute physiological and chronic health evaluation II (APACHE II) scores, and sepsis-related organ failure assessment (SOFA) scores were significantly lower in the survival group compared with the death group (p < 0.05). In the survival group, neutrophils counts and NLR were much lower than those in the death group, while lymphocytes counts were much higher (p < 0.05). ROC curves showed that the optimal cut-off value for NLR to predict 90-day mortality in elderly patients with severe sepsis combined with DM was 3.482. Patients were divided into high NLR and low NLR groups based on whether NLR was ≥ 3.482. In terms of the log-rank test results, patients in the low NLR group had a significantly higher 90-day survival rate than those in the high NLR group (Logrank χ2 = 8.635, p = 0.003). The multivariate cox regression model showed that the length of ICU stay longer than 15 days and NLR ≥ 3.482 were independent risk factors for 90-day prognosis in elderly patients with severe sepsis combined with DM.NLR ≥ 3.482 can be used to predict whether poor prognosis occurs in the short term after illness in elderly patients with severe sepsis combined with DM, and has good assessment value.

&amp;#160; &amp;#160; &amp;#160;The collision between the Indian and Eurasian plates in the Cenozoic eras resulted in the formation of the world's largest and highest plateau. The intensive collision, subduction, and related deep dynamic processes led to significant crustal shortening, uplifting, and expansion of the Plateau, accompanied by eastward extrusion of plateau materials. The southeastern Tibetan Plateau (SETP) is one of the most important channels for escaping plateau materials. The widespread existence of crustal weak material flow in the SETP has become widely accepted. However, previous research has mostly been limited to two-dimensional profiles or spaced data measurement points. Therefore, obtaining reliable and high-resolution geophysical models of the lithosphere is crucial for understanding the deformation mechanisms of the plateau.&amp;#160; &amp;#160; Our three-dimensional resistivity model shows unprecedented resolution of the Simao Block of the Indochina Block, offering new insights into the material transport and deformation mechanisms of the SETP. Two consecutive large-scale high-conductivity anomalies observed in the middle-lower crust are speculated to be partial melting associated with crustal flow. The rigid lithosphere separated by significant strike-slip faults on the SETP may be pulled by ductile materials flow, where plastic flows in the middle-lower crust drive the rigid blocks to extrude and escape along the boundary faults, thus dominating the deformation of the lithosphere. The large-scale delamination of the continental lithosphere leads to upwelling of the asthenosphere along mechanically weak areas. Upwelling hot materials continue to heat the entire crust, and the expanding and diffusing lower crust further accelerates partial melting and plastic flow in the middle-lower crust.

Protein structure-based property prediction has emerged as a promising approach for various biological tasks, such as protein function prediction and sub-cellular location estimation. The existing methods highly rely on experimental protein structure data and fail in scenarios where these data are unavailable. Predicted protein structures from AI tools (e.g., AlphaFold2) were utilized as alternatives. However, we observed that current practices, which simply employ accurately predicted structures during inference, suffer from notable degradation in prediction accuracy. While similar phenomena have been extensively studied in general fields (e.g., Computer Vision) as model robustness, their impact on protein property prediction remains unexplored. In this paper, we first investigate the reason behind the performance decrease when utilizing predicted structures, attributing it to the structure embedding bias from the perspective of structure representation learning. To study this problem, we identify a Protein 3D Graph Structure Learning Problem for Robust Protein Property Prediction (PGSL-RP3), collect benchmark datasets, and present a protein Structure embedding Alignment Optimization framework (SAO) to mitigate the problem of structure embedding bias between the predicted and experimental protein structures. Extensive experiments have shown that our framework is model-agnostic and effective in improving the property prediction of both predicted structures and experimental structures.

Detecting objects accurately from a large or open vocabulary necessitates the vision-language alignment on region representations. However, learning such a region-text alignment by obtaining high-quality box annotations with text labels or descriptions is expensive and infeasible. In contrast, collecting image-text pairs is simpler but lacks precise object location information to associate regions with texts. In this paper, we propose a novel approach called Contrastive Language-Image Mosaic (CLIM), which leverages large-scale image-text pairs effectively for aligning region and text representations. CLIM combines multiple images into a mosaicked image and treats each image as a ‘pseudo region’. The feature of each pseudo region is extracted and trained to be similar to the corresponding text embedding while dissimilar from others by a contrastive loss, enabling the model to learn the region-text alignment without costly box annotations. As a generally applicable approach, CLIM consistently improves different open-vocabulary object detection methods that use caption supervision. Furthermore, CLIM can effectively enhance the region representation of vision-language models, thus providing stronger backbones for open-vocabulary object detectors. Our experimental results demonstrate that CLIM improves different baseline open-vocabulary object detectors by a large margin on both OV-COCO and OV-LVIS benchmarks. The code is available at https://github.com/wusize/CLIM.

Objective Evidence regarding the effects of particulate matter (PM) pollutants on cardiovascular disease (CVD) mortality remains limited in Shanghai, China. Our objective was to thoroughly evaluate associations between PM pollutants and CVD mortality. Methods Daily data on CVD mortality, PM (PM 10 and PM 2.5 ) pollutants, and meteorological variables in Shanghai, China were gathered from 2003 to 2020. We utilized a time-series design with the generalized additive model to assess associations between PM pollutants and CVD mortality. Additionally, we conducted stratified analyses based on sex, age, education, and seasons using the same model. Results We found that PM pollutants had a significant association with CVD mortality during the study period. Specifically, there was a 0.29% (95%CI: 0.14, 0.44) increase in CVD mortality for every 10 μg/m3 rise in a 2-day average (lag01) concentration of PM 10 . A 0.28% (95% CI: 0.07, 0.49) increase in CVD mortality was associated with every 10 μg/m3 rise in PM 2.5 concentration at lag01. Overall, the estimated effects of PM 10 and PM 2.5 were larger in the warm period compared with the cold period. Furthermore, males and the older adult exhibited greater susceptibility to PM 10 and PM 2.5 exposure, and individuals with lower education levels experienced more significant effects from PM 10 and PM 2.5 than those with higher education levels. Conclusion Our findings suggested that PM pollutants have a substantial impact on increasing CVD mortality in Shanghai, China. Moreover, the impacts of air pollution on health may be altered by factors such as season, sex, age, and educational levels.